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Moving Beyond p < 0.05 in Ecotoxicology: A Guide for Practitioners.
Erickson, Richard A; Rattner, Barnett A.
Afiliación
  • Erickson RA; Upper Midwest Environmental Sciences Center, US Geological Survey, La Crosse, Wisconsin.
  • Rattner BA; Patuxent Wildlife Research Center, US Geological Survey, Beltsville, Maryland.
Environ Toxicol Chem ; 39(9): 1657-1669, 2020 09.
Article en En | MEDLINE | ID: mdl-32539165
Statistical inferences play a critical role in ecotoxicology. Historically, null hypothesis significance testing (NHST) has been the dominant method for inference in ecotoxicology. As a brief and informal definition of NHST, researchers compare (or "test") an experimental treatment or observation against a hypothesis of no relationship (the "null hypothesis") using the collected data to see if the observed values are statistically "significant" given predefined error rates. The resulting probability of observing a value equal to or greater than the observed value assuming the null hypothesis is true is the p value. Criticisms of NHST have existed for almost a century and have recently grown to the point where statisticians, including the American Statistical Association (ASA), have felt the need to clarify the role of NHST and p values beyond their current common use. These limitations also exist in ecotoxicology. For example, a review of the 2010 Environmental Toxicology & Chemistry (ET&C) volume that found many authors did not correctly report p values. We repeated this review looking at the 2019 volume of ET&C. Incorrect reporting of p values still occurred almost a decade later. Problems with NHST and p values highlight the need for statistical inferences besides NHST, something long known in ecotoxicology and the broader scientific and statistical communities. Furthermore, concerns such as these led the executive director of the ASA to recommend against use of "statistical significance" in 2019. In light of these criticisms, ecotoxicologists require alternative methods. We describe some alternative methods including confidence intervals, regression analysis, dose-response curves, Bayes factors, survival analysis, and model selection. Lastly, we provide insights for what ecotoxicology might look like in a post-p value world. Environ Toxicol Chem 2020;39:1657-1669. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Estadística como Asunto / Ecotoxicología Tipo de estudio: Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Animals Idioma: En Revista: Environ Toxicol Chem Año: 2020 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Estadística como Asunto / Ecotoxicología Tipo de estudio: Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Animals Idioma: En Revista: Environ Toxicol Chem Año: 2020 Tipo del documento: Article
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